1. Field
The present invention relates generally to consumer transactions in electronic commerce, and more specifically to techniques for tracking data using visible controls in web pages over a network.
2. Description of Related Art
Commercial transactions over the Internet commonly involve business entities that use websites as a platform to market a wide variety of products to consumers. One well known example of such a website is Amazon.com. A typical transaction involves a consumer visiting the Amazon.com website and conducting a query. The user may insert information about a product of interest, as a result of which the user may receive a list of results. These results may include, for example, identities of specific products, prices of the products, features and specifications of the products, and other such attributes. Thereupon, the user may purchase the product by providing information to the website such as a name, address, credit card number, and the like.
Particularly for the consumer who tends to conducts a fair amount of business transactions over the Internet, keeping track of different items on different websites presents unique challenges. For instance, a consumer may place a first item of interest in a shopping cart on a first eCommerce site, a second item of interest in a wish list of a second e-commerce site, and a third item of interest obtained from a query on a third eCommerce site in a file on the user's computer, all with the intention of returning later to make purchasing decisions regarding each of these items. It may, however, be unduly time consuming and duplicative for the consumer to later have to revisit the three sources in order to review the selected items in the course of the decision-making process.
Further, if the consumer had not saved the item in a shopping cart or similar feature on a website, he or she may have to run another query in an attempt to find the item. If the consumer cannot remember the query, the consumer may be relegated to attempting another query. A subsequent query which is not precisely the same as the query executed before, however, may not bring up the originally desired item at the originally desired price. The net result is that the consumer may have to either pay more, lose out on an item, or spend more time completing his transactions.
These examples demonstrate that, as the frequency of a consumer's reliance on eCommerce transactions increases, so too increases the challenge for the consumer to efficiently and accurately to keep track of goods and services of interest to him or her.
The problem is exacerbated where characteristics of a good or service of interest tend to change over time. Many exemplary domains within eCommerce involve goods or services having fluctuating characteristics. One such example is the travel industry. Numerous types of “travel agent” websites exist, such as, for instance, Expedia.com. In addition, airlines often maintain there own websites (e.g. Continental.com) where tickets are sold directly from the airline. In travel websites of these types, myriad options are available to search for information about characteristics of travel assets. Such characteristics may include price and availability for an airline ticket, hotel reservation, and car rental, and like characteristics.
Travel asset characteristics are highly volatile. That is, price, availability, and other characteristics of travel assets tend to change over time. As such, users may desire the ability to track a particular target asset over time. Tracking a target asset typically requires repeatedly visiting a website in order to continually request travel information. Executing multiple queries at multiple times can be difficult and time consuming. This is especially true if the user desires to track more than one item and is targeting assets from more than one website. In these types of situations, valuable information regarding the best deals, optimal travel times, etc. may simply be lost in the mix.
Yet an additional obstacle compounding these difficulties relates to the inefficiency of using information from a first website at a second website. As an illustration a user may visit an online travel agency and find a desired fare. The fare may include a service fee charged by the online travel agency that the user may not otherwise have to pay by purchasing the ticket directly from the airline. The user, having already queried the site that assesses the service charge, may be required to re-enter the query at the airline's website to determine the fare for the ticket. The new search may require entering the ticket information at the airline website in a format which may be different from that of the travel agent website. Such activity may lead to user frustration. Users may be unwilling to spend the extra time conducting multiple queries to find the lowest fare. In short, these and other problems may result in an overall inefficiency and a lack of cohesiveness for consumers monitoring transactional-based data over the Internet.
As a result, a need exists for new techniques for identifying both fixed and volatile assets on the internet, and for streamlining the electronic purchasing process that overcomes the above stated problems with the present state of the art.